Apart from simple diagnosis, the study takes an important step toward predictive health monitoring by modeling the risk of ...

In the current era of big data, the volume of information continues to grow at an unprecedented rate, giving rise to the crucial need for efficient ...

The proposed method employs a new sparse Bayesian learning algorithm based on coupled hyperblocks to estimate unknown switching instants. Experimental results on benchmark artificial and real networks ...

Learning Bayesian network from data is a non-deterministic polynomial-time (NP) hard problem. Experts’ knowledge is beneficial to determine the BN structure. In this paper, we propose a novel ...

INNOptimizer is using latest Bayesian Optimization algorithms and a broad set of analytical tools to guide optimizations with minimum experimentation needed. Don't waste time and money with poor ...